Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

Prior research highlights the benefits of multimode surveys and best practices for item-by-item (IBI) and matrix-type survey items. Some researchers have explored whether mode differences for online and paper surveys persist for these survey item types. However, no studies discuss measurement invariance when both item types and online modes are…

The application of diagnostic classification models (DCMs) in the field of educational measurement is getting more attention in recent years. To make a valid inference from the model, it is important to ensure that the model fits the data. The purpose of the present study was to investigate the performance of the limited information…

Previous research has individually assessed parallel analysis and minimum average partial for factor retention in exploratory factor analysis using ordinal variables. The current study is a comprehensive simulation study including the manipulation of eight conditions (type of correlation matrix, sample size, number of variables per factor, number…

As the international large-scale assessments (ILSAs) become more popular, policy makers and education practitioners are interested in collecting as much student background information as possible to better understand the learning context of their students. To collect such abundant information, administrators need to develop a lot of questions.…

Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

As educators and school leaders work towards building students' capacity throughout a student's academic career, the goal is to facilitate opportunities for students to develop college and career readiness skills that can be applied to novel and challenging problems long after high school graduation. Hess' Cognitive Rigor Matrix (HCRM) is a tool…

Down Syndrome (DS) is an intellectual disability (ID) characterized by a distinct profile of behavioral characteristics that impact language learning. One specific area of challenge is moving from producing single words to producing more complex syntax. Although there is a broad evidence base for existing interventions for children with DS,…

The field of deafblind (DB) education has a long and rich history which includes a lack of qualified personnel to meet the needs of the population of learners. In addition, the literature base is small, lacking evidence for effective practices or methods of assessing and tracking growth with these learners. The ability to adequately track student…

To best support all students' academic, behavioral, and social needs, an integrated systems approach is necessary. In such systems, all faculty and staff ideally recognize student success is a shared responsibility and collaborate in a data-informed process to define common student behavioral expectations to facilitate success academically,…